composite_analysis

composite_analysis(
    data,
    families,
    composite_type='CompetingRisks',
    average_method='AIC',
    sampler='DEMCz',
    iterations=3000,
    output_length=10000,
    credible_level=0.9,
    seed=12345,
    exceedance_probabilities=None,
    thinning_interval=-1,
)

Composite frequency analysis over one child analysis per families entry.

Combines the child univariate frequency analyses (each fit to data) into a single composite curve. Wraps the shared C++ CompositeAnalysis.

Parameters

Name	Type	Description	Default
data	array_like	Observations to fit.	required
families	sequence of str	Distribution family name of each child analysis.	required
composite_type	('CompetingRisks', 'Mixture', 'ModelAverage')	How the child curves are combined.	"CompetingRisks"
average_method	str	Selects the model-averaging criterion.	"AIC"
sampler	('DEMCz', 'DEMCzs', 'ARWMH', 'NUTS')	MCMC sampler.	"DEMCz"
iterations	int	Number of post-warmup MCMC iterations.	3000
output_length	int	Number of posterior samples used to build the credible band.	10000
credible_level	float	Credible-interval width.	0.90
seed	int	PRNG seed for the sampler.	12345
exceedance_probabilities	array_like of float	Exceedance probabilities at which to tabulate the curve; when None, the default ordinates are used.	None
thinning_interval	int	MCMC thinning interval; -1 keeps the sampler’s own default.	-1

Returns

Name	Type	Description
	dict	The same shape as univariate_analysis: parameters, mode_curve, mean_curve, lower_ci, upper_ci, aic, bic, dic, rmse.

See Also

univariate_analysis